Assessment of social skills for developmental disorders by neuroscience-based EEG analysis

2019 Fiscal Year Final Research Report

• Project/Area Number: 17K00383
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Kansei informatics
• Research Institution: Kyushu Institute of Technology
• Principal Investigator: Kawano Hideaki 九州工業大学, 大学院工学研究院, 准教授 (00404096)
• Project Period (FY): 2017-04-01 – 2020-03-31
• Keywords: ASD / スパイキングニューラルネットワーク / ミラーニューロン / 運動 / 適応機能

Outline of Final Research Achievements

This study evaluated the effectiveness of an exercise on the people with autism spectrum disorder using a spiking neural network. We collected EEG patterns during perception and imitation of facial expressions for several emotions. Recently, some studies have been reported that mirror neuron system does not work well in the case of subjects with brain disorders. In this paper, we observed brain activities during perception and imitation of facial expressions in typically developed subjects, ASD subjects who exercise regularly, and ASD subjects who don’t exercise regularly. There was little difference between healthy subjects and ASD subjects with regular exercises, though ASD subjects who don't exercise regularly exhibit significant difference. The results show the effectiveness of regular exercise on autism spectrum disorder.

Free Research Field

ソフトコンピューティング

Academic Significance and Societal Importance of the Research Achievements

現状，ASDの適応機能は，行動観察に基づく診断で行われており，脳活動からの定量的な判定を行うシステムは存在しない．本研究で開発したASDの適応機能評価システムは，他に例を見ない新規の試みであり，大型の装置を必要とせずオンサイトでの評価が可能となる点で実用的な意義は大きい．また，ASDに運動が及ぼす効果を定量的に評価した先行研究は存在せず，本研究の学術的な意義は大きい．この方法論を活用することで，運動プログラムの設計，すなわち適度な運動頻度や運動量の指針が明らかになり， 脳機能障害を改善する様々な運動プログラムの開発に寄与することが期待され，今後の発展性のある研究と言える.